Device and Method for Providing User Interface for Providing Mental Health Information

This application claims the benefit of priority to: Korean Patent Application No. KR1020240057146 entitled “DEVICE AND METHOD FOR PROVIDING USER INTERFACE FOR PROVIDING MENTAL HEALTH INFORMATION,” filed on Oct. 24, 2022; and PCT Application No. PCT/KR 2023/010029 entitled “DEVICE AND METHOD FOR PROVIDING USER INTERFACE FOR PROVIDING MENTAL HEALTH INFORMATION,” filed on Jul. 13, 2023.

All the aforementioned applications are hereby incorporated by reference in their entirety.

The present disclosure relates to a device and method for providing a user interface for mental health information providing service.

As the service industry develops and the number of emotional labor workers increases, the number of people suffering from mental stress and depression is increasing. As we enter an aging society, the number of people suffering from cognitive dysfunction such as dementia is also increasing. Recently, this phenomenon has been recognized as a social problem, and various studies are being conducted to diagnose, prevent, and treat mental health to solve this problem.

For example, a technology has been disclosed that acquires frontal lobe brain wave data of the user from an electroencephalography (EEG) measuring device and measures depression severity of the user by analyzing the frontal lobe brain wave data.

However, even when mental health is diagnosed through these technologies, there is a problem that users cannot easily understand the diagnosis results that include professional terms. In addition, there is a problem that the evaluation of mental health is only valuable as an evaluation because it is not known what response to take based on the diagnosis results.

The background technology of the present disclosure has been written to facilitate understanding of the present disclosure. It should not be understood that the matters described in the background technology of the disclosure are recognized as prior art.

Accordingly, there is a need for a method to provide the results of mental health diagnoses, such as depression, stress-related mental health, and dementia, in a form that is easier for the general public to understand.

As a result, the inventors of the present disclosure attempted to develop a method and a device for performing the same capable of calculating result values of a plurality of indicators related to mind health and mental health using a user's biometric data and summarizing and providing readable information on mind health and mental health.

The tasks of the present disclosure are not limited to the tasks mentioned above, and other tasks not mentioned will be clearly understood by those skilled in the art from the description below.

In order to solve the above-described problem, a method performed by a processor of a mental health information providing device for providing a user interface for providing mental health information according to one embodiment of the present disclosure is provided. The method includes obtaining brain wave data and heartbeat data of a user, calculating a brain health index representing brain activity, brain flexibility, brain intelligence, and brain balance based on the brain wave data and calculating a mental health index representing autonomic nerve activity, autonomic nerve balance, and stress based on the heartbeat data, and providing a service interface screen that graphically visualizes the calculated brain health index and mental health index.

According to another aspect of the present disclosure, the service interface screen may include a region that displays an activation level of each frequency band of Delta wave, Theta wave, Low-Alpha, High-Alpha, Low-Beta, Middle-Beta, High-Beta, Gamma calculated based on the brain wave data as a graph for the brain activity.

According to still another aspect of the present disclosure, the service interface screen may include a region where the brain activation level by each frequency band is displayed in different colors in the graph for the brain activity and a normal range region is displayed on a reference axis representing the brain activation level by each frequency band.

According to still another aspect of the present disclosure, the calculating may include further includes comparing a brain activation level of each of a plurality of frequency bands with a preset reference value, and generating a brain-related diagnosis result of a user based on a comparison result, and the interface screen may include a region representing the diagnosis result in a region adjacent to the graph for the brain activity.

According to still another aspect of the present disclosure, the service interface screen may include a region that represents connection strength between the brain regions calculated based on the brain wave data as a continuous spectrum graph for the brain flexibility.

According to still another aspect of the present disclosure, the service interface screen may include a region where the connection strength is displayed at one point in the continuous spectrum corresponding to the brain flexibility, and brain network images corresponding to the reference values of the continuous spectrum are displayed.

2 According to still another aspect of the present disclosure, the service interface screen may include a region where a peak value of any one frequency band calculated based on the brain wave data is represented as a graph for the brain intelligence in a quadrant representing a frequency and an output value (μV) of the frequency.

According to still another aspect of the present disclosure, the service interface screen may include a region that represents a prefrontal activation asymmetry index calculated based on the brain wave data as a semicircular scale graph for the brain balance.

According to still another aspect of the present disclosure, the service interface screen may include a region that is configured such that the prefrontal activation asymmetry index points to a point on a semicircular scale corresponding to left and right prefrontal activation levels and that behavioral characteristic information according to asymmetry on the semicircular scale is displayed at both ends.

According to still another aspect of the present disclosure, the method may further include, after the obtaining, extracting heart rate variability (HRV) data for calculating the mental health index based on the heartbeat data.

According to still another aspect of the present disclosure, the service interface screen may include a region that displays an activation level of each component of a very low frequency (VLF), a low frequency (LF), a high frequency (HF), and total power (TP) (including VLF, LF, and HF) calculated based on the heart rate variability data as a graph for the autonomic nerve activity.

According to still another aspect of the present disclosure, the service interface screen may include a region where the activation level is displayed in different colors in a graph for the autonomic nerve activity and a normal range region is displayed on a reference axis representing the activation level.

According to still another aspect of the present disclosure, the service interface screen may include a region where the diagnosis result related to the autonomic nerve activity is displayed in a region adjacent to the graph for the autonomic nerve activity.

According to still another aspect of the present disclosure, the service interface screen may include a region that displays sympathetic and parasympathetic nerve activity calculated based on the heart rate variability data as a percentage ratio in a comparison graph with respect to the autonomic nerve balance.

According to still another aspect of the present disclosure, the service interface screen may include a region where each percentage ratio in the comparison graph for the autonomic nerve balance is displayed as a bar scale, and abnormal phenomenon information according to imbalance of the sympathetic and parasympathetic nerve activity is displayed at both ends.

According to still another aspect of the present disclosure, the service interface screen may include a region that displays a stress index and stress resistance calculated based on the heart rate variability data as a continuous spectrum graph for the stress state.

According to still another aspect of the present disclosure, the service interface screen may include a region where the stress index and the stress resistance are displayed at one point in a continuous spectrum corresponding to the stress state.

According to still another aspect of the present disclosure, the method may further include, before the calculating, obtaining psychological test result data of the user, and the service interface screen may include a region that represents a numerical value corresponding to the test result data as a continuous spectrum graph for subjective psychological state.

According to still another aspect of the present disclosure, the calculating may further include generating a self-understanding value of the user based on the heart rate variability data and the psychological test result data, and the service interface screen may include a region that a continuous spectrum graph for self-understanding is placed in a region adjacent to a graph related to the mental health index, and the self-understanding value is displayed at one point in the continuous spectrum.

According to still another aspect of the present disclosure, the service interface screen may include a region where graphic objects representing diagnosis results of each of the brain health index representing the brain activity, brain flexibility, brain intelligence, and brain balance, and the mental health index representing the autonomic nerve activity, autonomic nerve balance, stress, and subjective psychological state are displayed.

In order to solve the above-described problem, a mental health information providing device according to another embodiment of the present disclosure is provided. The device includes a communication interface, a memory, and a processor operably connected to the communication interface and the memory, in which the processor is configured to obtain brain wave data and heartbeat data of a user, calculate a brain health index representing brain activity, brain flexibility, brain intelligence, and brain balance based on the brain wave data, calculate a mental health index representing autonomic nerve activity, autonomic nerve balance, and stress based on the heartbeat data, and provide a service interface screen that graphically visualizes the calculated brain health index and mental health index.

Specific details of other embodiments are included in the detailed description and drawings.

According to the present disclosure, it is possible to accurately calculate brain health indices such as brain activity, brain flexibility, brain intelligence, and brain balance by using brain wave data acquired from a sensor that measures brain wave signals.

In addition, according to the present disclosure, it is possible to accurately calculate mental health indices such as autonomic nerve activity, autonomic nerve balance, and stress by using heartbeat data obtained from a sensor that measures heartbeat.

In particular, the present disclosure can help with stress assessment of high-risk occupational groups, stress management of workers in the workplace, preventive medical management of mental health, and rapid evaluation (diagnosis) by medical staff by numerically expressing a person's mental and emotional state as a brain health index and a mental health index. Further, the present disclosure can be utilized as a means for preventing diseases and accidents (for example, health checkup records for insurance subscription) depending on the user's current condition.

In addition, the present disclosure can help users understand their current mental health status by simplifying and expressing the professional diagnosis region in a graph.

In addition, the present disclosure can provide users with meaningful information for real life, rather than just simple diagnosis results, by providing detailed descriptions of diagnosis contents, symptoms, treatment contents, or the like through the user interface.

The effects according to the present disclosure are not limited to those exemplified above, and more diverse effects are included in the present disclosure.

The advantages and features of the present disclosure, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in various different forms, and these embodiments are provided only to make the disclosure of the present disclosure complete and to fully inform those skilled in the art of the scope of the disclosure. In connection with the description of the drawings, similar reference numerals may be used for similar components.

In this document, the expressions “have”, “can have”, “include”, or “may include” indicate the presence of a given feature (for example, a numerical value, function, operation, or component such as a part), but do not exclude the presence of additional features.

In this document, the expressions “A or B”, “at least one of A and/or B”, or “one or more of A or/and B” can include all possible combinations of the listed items. For example, “A or B”, “at least one of A and B”, or “at least one of A or B” may all refer to (1) including at least one A, (2) including at least one B, or (3) including both at least one A and at least one B.

The expressions “first”, “second”, “first”, or “second”, or the like, used in this document can describe various components, regardless of order and/or priority, and are only used to distinguish one component from another, but do not limit the components. For example, a first user device and a second user device can represent different user devices, regardless of order or priority. For example, without departing from the scope of the rights set forth in this document, a first component can be referred to as a second component, and similarly, a second component can also be referred to as a first component.

When it is stated that a component (for example, a first component) is “(operatively or communicatively) coupled with/to” or “connected to” another component (for example, a second component), it should be understood that the component can be directly coupled to the other component, or can be connected via another component (for example, a third component). Conversely, when it is stated that a component (for example, a first component) is “directly coupled with” or “directly connected to” another component (for example, a second component), it should be understood that no other component (for example, a third component) exists between the component and the other component.

The expression “configured (or set) to” as used herein may be used interchangeably with, for example, “suitable for”, “having the capacity to”, “designed to”, “adapted to”, “made to”, or “capable of”. Moreover, the term “configured (set) to” does not necessarily mean something is “specifically designed to” in terms of hardware. Instead, in some contexts, the expression “a device configured to” can mean that the device is “capable of” doing something together with other devices or components. For example, the phrase “a processor configured (or set) to perform A, B, and C” can mean a dedicated processor (for example, an embedded processor) to perform those operations, or a generic-purpose processor (for example, a CPU or an application processor) that can perform those operations by executing one or more software programs stored in a memory device.

The terms used in the present document are only used to describe specific embodiments and may not be intended to limit the scope of other embodiments. The singular expression may include the plural expression unless the context clearly indicates otherwise. The terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person of ordinary skill in the art described in this document. Among the terms used in this document, terms defined in general dictionaries may be interpreted as having the same or similar meaning in the context of the related technology, and shall not be interpreted in an ideal or excessively formal meaning unless explicitly defined in this document. In some cases, even if a term is defined in this document, it cannot be interpreted to exclude the embodiments of this document.

The individual features of the various embodiments of the present disclosure may be partially or wholly combined or combined with each other, and as can be fully understood by those skilled in the art, various technical connections and operations are possible, and each embodiment may be implemented independently of each other or may be implemented together in a related relationship.

For clarity in the interpretation of this specification, the terms used in this specification are defined below.

As used herein, the term “brain wave data” may refer to EEG (electroencephalogram) signal values recorded by a sensor that detects brain waves. More specifically, the brain wave data may be a brain wave signal of a positive potential response that appears after a stimulus of a certain intensity.

Meanwhile, since the brain wave data may be a signal or a signal value obtained from a sensor, the brain wave data may be interpreted in the same meaning as sensor/sensing data.

According to a feature of the present disclosure, the brain wave data may include brain wave data measured from at least one electrode of Fp1, Fp2, F3, Fz, F4, F8, T7, C3, C4, Cz, T8, P7, P3, Pz, P4, P8, 01, 02, FCz, TP9, TP10, Oz, A Fz, F7, Fpz, AF7, AF3, AF4, AF8, F9, F5, F1, F2, F6, F10, FT9, FT7, FC5, FC3, FC1, FC2, FC4, FC6, FT8, FT10, C5, C1, C2, C6, TP7, CP5, CP3, CP1, CPz, CP2, CP4, CP6, TP8, P9, P5, P1, P2, P6, P10, PO9, PO7, PO3, POz, PO4, PO8, PO10, O9, Iz, O10, F11, F12, FT11, FT12, TP11, TP12, PO11, PO12, P11, P12, I11, I12 and IIz.

According to a feature of the present disclosure, the brain wave data may be brain wave data obtained in a resting state in which no stimulation is applied to an object, but is not limited thereto.

As used herein, the term “heartbeat data” may refer to electrocardiogram (ECG), blood pressure photoplethysmography (PPG) signal values recorded by a sensor that detects a heartbeat. More specifically, the heartbeat data may be data representing changes in, or variability in the time interval between heartbeats (between peaks).

Hereinafter, the present disclosure will be described in detail by explaining preferred embodiments of the present disclosure with reference to the attached drawings.

1 FIG. is a schematic diagram of a user interface providing system for providing mental health information according to one embodiment of the present disclosure.

1 FIG. 10 10 100 200 300 Referring to, a user interface providing system(hereinafter referred to as “mental health information system”) for providing mental health information according to one embodiment of the present disclosure may include a sensing devicefor measuring a user's biometric data, a user devicecarried by the user, and a user interface providing device (hereinafter referred to as “mental health information providing device”) for providing the user's brain and mental health information in the form of a user interface.

100 100 100 200 200 100 The sensing deviceis a device capable of acquiring the user's biometric data, and may include various devices capable of measuring the user's heartbeat depending on the type of biometric data. For example, the sensing devicemay be a wearable device worn on the user's wrist, and may acquire the user's electrocardiogram data through the wearable device. For another example, the sensing devicemay correspond to the user device, and may acquire the user's pulse data (photoplethysmography) based on the change in blood flow of the fingertips through the user device. For another example, the sensing devicemay be a patch-type device that adheres closely to the user's scalp, and may acquire the user's brain wave data through this.

In one embodiment of the present disclosure, biometric data related to the user's mental health may include data capable of extracting temporal variations of heartbeats rather than changes in heartbeat, that is, all types of biometric data capable of evaluating the balance between the sympathetic and parasympathetic nerves of the autonomic nervous system and the activity level of each.

200 200 100 300 300 The user deviceis a device possessed by the user that can check mental health information, and may include a smartphone, a tablet PC, a PC, a laptop, or the like. Specifically, the user devicemay transmit biometric data (brain wave data and heartbeat data) measured by the sensing deviceto the mental health information providing device, and may receive and output a user interface including a brain health index and a mental health index visualized as a graph from the mental health information providing device.

200 200 300 In various embodiments, the user devicemay output a psychological test interface for measuring the user's psychological state, such as depression or anxiety. For example, the user devicemay receive a questionnaire for the user's psychological test from the mental health information providing deviceand obtain the user's response thereto.

300 100 300 300 300 The mental health information providing devicemay include a general-purpose computer, a laptop, a data server, or the like that performs various operations to calculate the brain health index and mental health index of the user based on the biometric data (brain wave data and heartbeat data) measured by a sensing deviceand provide the calculated indices to the user in the form of a mental health information report. Specifically, the mental health information providing devicemay refine the brain wave data and heartbeat data into data forms for calculating the brain health index and the mental health index. For example, the mental health information providing devicemay filter the brain wave data to extract brain activity data for a specific frequency, and as another example, the mental health information providing devicemay extract heart rate variability (HRV) data from the heartbeat data.

300 300 200 The mental health information providing devicemay provide the user interface that outputs information related to the brain health index and the mental health index. For example, the mental health information providing devicemay provide a mobile or web application/program that can be installed or executed by the user device, and may visually provide the user's mental health information through the mobile or web application/program.

1000 200 2 FIG. So far, the mental health information systemaccording to one embodiment of the present disclosure has been described, and below, the user devicethat outputs a user interface screen for the mental health information will be described with reference to.

2 FIG. is a schematic diagram illustrating the configuration of the user device according to one embodiment of the present disclosure.

2 FIG. 200 210 220 230 200 Referring to, the user devicemay include a memory interface, one or more processors, and a peripheral interface. Various components within the user devicemay be connected by one or more communication buses or signal lines.

210 250 220 250 The memory interfaceis connected to the memoryand may transmit various data to the processor. Here, the memorycan include at least one type of storage medium among a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, an SD or XD memory, or the like), a RAM, an SRAM, a ROM, an EEPROM, a PROM, a network storage, a cloud, and a blockchain database.

250 250 In various embodiments, the memorymay store the user's biometric data (brain wave data and heartbeat data) and the user's psychological test result data. In addition, the memorymay store each configuration of a user interface for outputting the user's brain health index and mental health index calculated based on the biometric data and psychological test result data.

250 251 252 253 254 255 256 251 252 253 254 292 255 256 100 256 1 256 2 250 In various embodiments, the memorymay store at least one of an operating system, a communication module, a graphical user interface module GUI, a sensor processing module, a telephone module, and an application module. Specifically, the operating systemmay include instructions for processing basic system services and instructions for performing hardware operations. The communication modulemay communicate with at least one of other ore or more devices, computers, and servers. The graphical user interface module GUImay process a graphical user interface. The sensor processing modulemay process sensor-related functions (for example, processing voice input received via one or more microphones). The telephone modulemay process telephone-related functions. The application modulemay perform various functions of a user application, such as electronic messaging, web browsing, media processing, navigation, imaging, and other processing functions. In addition, the user devicemay store one or more software applications-and-(for example, an application for providing mental health information) associated with one type of service in the memory.

250 257 258 In various embodiments, the memorymay store a digital assistant client module(hereinafter, DA client module), and thereby store instructions for performing client-side functions of the digital assistant and various user data(for example, user-customized vocabulary data, preference data, other data such as the user's electronic address book, or the like).

257 240 200 Meanwhile, the DA client modulemay obtain the user's voice input, text input, touch input, and/or gesture input through various user interfaces (for example, I/O subsystem) provided in the user device.

257 257 257 280 In addition, the DA client modulemay output data in audiovisual and tactile forms. For example, the DA client modulemay output data consisting of a combination of at least two or more of voice, sound, notification, text message, menu, graphic, video, animation, and vibration. In addition, the DA client modulemay communicate with a digital assistant server (not illustrated) using a communication subsystem.

257 200 257 200 200 200 In various embodiments, the DA client modulemay collect additional information about the surroundings of the user devicefrom various sensors, subsystems, and peripheral devices to construct a context associated with the user input. For example, the DA client modulemay provide context information along with the user input to a digital assistant server to infer the user's intent. Here, the context information that may accompany the user input may include sensor information, such as lighting, ambient noise, ambient temperature, images of the surroundings, videos, or the like. As another example, the context information may include a physical state (for example, device orientation, device position, device temperature, power level, speed, acceleration, motion patterns, cellular signal strength, or the like) of the user device. As yet another example, the context information may include information (for example, processes running on the user device, installed programs, past and present network activity, background services, error logs, resource usage, or the like) related to software state of the user device.

250 200 2 FIG. In various embodiments, the memorymay include additional or deleted instructions, and further, the user devicemay include additional configurations other than those illustrated in, or may exclude some configurations.

220 200 250 The processormay control the overall operation of the user deviceand execute various commands to implement the user interface that provides the mental health information by running an application or program stored in the memory.

220 220 The processormay correspond to a computational device such as a central processing unit (CPU) or an application processor (AP). In addition, the processormay be implemented in the form of an integrated chip IC such as a System on Chip (SoC) in which various computational devices that perform machine learning, such as a neural processing unit (NPU), are integrated.

220 In various embodiments, the processormay obtain the user's biometric data (brain wave data and heartbeat data), output the user interface screen graphically visualizing the mental health index and brain health index calculated based on the biometric data, and provide various contents (detailed description of diagnosis, symptoms, treatment contents) related to the mental health index and brain health index according to the user's interaction.

230 200 200 220 The peripheral interfacemay be connected to various sensors, subsystems, and peripheral devices to provide data so that the user devicecan perform various functions. Here, it can be understood that the user deviceperforms a certain function as being performed by the processor.

230 260 261 262 200 230 263 200 263 The peripheral interfacemay receive data from a motion sensor, a light sensor (illumination sensor), and a proximity sensor, through which the user devicemay perform orientation, light, and proximity detection functions, or the like. For another example, the peripheral interfacemay receive data from other sensors(positioning system-GPS receiver, temperature sensor, biometric sensor), through which the user devicemay perform functions related to the other sensors.

200 270 230 271 200 In various embodiments, the user devicemay include a camera subsystemconnected to the peripheral interfaceand an optical sensorconnected thereto, which enables the user deviceto perform various photographing functions, such as taking pictures and recording video clips.

200 280 230 280 In various embodiments, the user devicemay include a communication subsystemcoupled with a peripheral interface. The communication subsystemmay include one or more wired/wireless networks and may include various communication ports, radio frequency transceivers, and optical transceivers.

200 290 230 290 291 292 200 In various embodiments, the user deviceincludes an audio subsystemcoupled to the peripheral interface, the audio subsystemincluding one or more speakersand one or more microphones, such that the user devicemay perform voice-activated functions, such as voice recognition, voice replication, digital recording, and telephony.

200 240 230 240 243 200 241 241 240 244 200 242 242 In various embodiments, the user devicemay include an I/O subsystemcoupled with the peripheral interface. For example, the I/O subsystemmay control a touch screenincluded in the user devicevia a touch screen controller. For example, the touch screen controllermay detect a user's contact and movement or cessation of contact and movement using any one of a plurality of touch sensing technologies, such as capacitive, resistive, infrared, surface acoustic wave technology, proximity sensor array, or the like. In another example, the I/O subsystemmay control other input/control devicesincluded in the user devicevia other input controller(s). As an example, the other input controller(s)may control one or more buttons, rocker switches, thumb-wheels, infrared ports, USB ports, and pointer devices such as a stylus.

200 300 3 5 FIGS.toF So far, the user deviceaccording to one embodiment of the present disclosure has been described, and below, the mental health information providing devicethat provides a service of visually refining the mental health information will be described with reference to.

3 FIG. is a block diagram illustrating the configuration of the mental health information providing device according to one embodiment of the present disclosure.

3 FIG. 300 310 320 330 340 Referring to, the mental health information providing devicemay include a communication interface, a memory, an I/O interface, and a processor, and each component may communicate with each other through one or more communication buses or signal lines.

310 100 200 310 100 200 310 200 The communication interfacemay be connected to the sensing deviceand the user devicevia a wired/wireless communication network to exchange data. For example, the communication interfacemay receive biometric data about a specific user from the sensing deviceand the user device. As another example, the communication interfacemay transmit a user interface that graphically visualizes mental health information to the user device.

310 311 312 311 312 Meanwhile, the communication interfacethat enables transmission and reception of such data includes a wired communication portand a wireless circuit, in which the wired communication portmay include one or more wired interfaces, for example, Ethernet, a universal serial bus USB, FireWire, or the like. In addition, the wireless circuitmay transmit and receive data with an external device via an RF signal or an optical signal. In addition, the wireless communication may use at least one of a plurality of communication standards, protocols, and technologies, for example, GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, and Wi-MAX, or any other suitable communication protocol.

320 300 320 The memorymay store various data used in the mental health information providing device. For example, the memorymay store user-specific biometric data (brain wave data and heartbeat data), brain health index and mental health index distribution results of users, or the like.

320 320 In various embodiments, the memorymay include a volatile or nonvolatile storage medium capable of storing various data, commands, and information. For example, the memorymay include at least one type of storage medium among a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, an SD or XD memory, or the like), a RAM, an SRAM, a ROM, an EEPROM, a PROM, a network storage, a cloud, and a blockchain database.

320 321 322 323 324 In various embodiments, the memorymay store configurations of at least one of an operating system, a communication module, a user interface module, and one or more applications.

321 The operating system(for example, embedded operating systems such as LINUX, UNIX, MAC OS, WINDOWS, VxWorks, or the like) may include various software components and drivers to control and manage general system operations (for example, memory management, storage device control, power management, or the like) and may support communication between various hardware, firmware, and software components.

323 310 220 311 312 310 The communication modulemay support communication with other devices through the communication interface. The communication modulemay include various software components for processing data received by the wired communication portor wireless circuitof the communication interface.

323 330 The user interface modulemay receive a user's request or input from a keyboard, touch screen, mouse, microphone, or the like through an I/O interfaceand provide the user interface on the display.

324 340 The applicationmay include a program or module configured to be executed by one or more processors. Here, the application for providing the mental health information may be implemented on a server farm.

330 300 323 330 323 The I/O interfacemay connect at least one of input/output devices (not illustrated) of the mental health information providing device, such as a display, a keyboard, a touch screen, and a microphone, to the user interface module. The I/O interfacemay receive user input (for example, voice input, keyboard input, touch input, or the like) together with the user interface moduleand process the command according to the received input.

340 310 320 330 300 320 The processoris connected to the communication interface, the memory, and the I/O interfaceto control the overall operation of the mental health information providing device, and may perform various commands for extracting standard plane information from an ultrasound image through an application or program stored in the memory.

340 340 340 The processormay correspond to a computational device such as a central processing unit (CPU) or an application processor (AP). In addition, the processormay be implemented in the form of an integrated chip (IC) such as a system on chip (SOC) in which various computational devices are integrated. Alternatively, the processormay include a module for calculating an artificial neural network model such as a neural processing unit (NPU).

4 5 FIGS.toF 340 300 Hereinafter, with reference to, a method for providing the user interface for providing the mental health information by the processorof the mental health information providing devicewill be described.

4 FIG. is a schematic flowchart of a method for providing the mental health information according to one embodiment of the present disclosure.

4 FIG. 340 110 340 200 340 100 Referring to, the processormay obtain the user's brain wave data and heartbeat data (S). Specifically, the processormay obtain the user's heartbeat data from the user device. The processormay obtain the user's brain wave data from the sensing device.

340 200 340 200 In various embodiments, the processormay further obtain the user's psychological test result data from the user device. Specifically, the processormay provide the user devicewith a psychological test interface including questions for the user's psychological test, thereby obtaining data for determining the user's psychological state, such as depression or anxiety.

340 340 In various embodiments, the processormay extract brain activity data of the user for any one region based on the user's brain wave data. For example, the processormay obtain brain activity data divided into a specific frequency region, for example, a delta wave of 1 to 4 Hz (a theta wave of δ4 to 8 Hz (a low-alpha wave (Lα) of θ8 to 10 Hz), a high-alpha wave (Hα) of 10 to 12 Hz, a low-beta wave (Lβ) of 12 to 15 Hz, a middle-beta wave (Mβ) of 15 to 20 Hz, a high-beta wave (Hβ) of 20 to 30 Hz, and a gamma wave (γ) of 30 to 50 Hz), as data for calculating the brain health index.

340 340 In various embodiments, the processormay extract heart rate variability (HRV) data based on the user's heartbeat data. More specifically, since the heart rate variability is an indicator that may predict cardiovascular function in response to stress or anxiety, the processormay extract values corresponding to components of a very low frequency (VLF) of 0 to 0.04 Hz, a low frequency (LF) of 0.04 to 0.15 Hz, and a high frequency (HF) of 0.15 to 0.4 Hz, and TP (total power; sum of HF, LF, VLF, or the like) from the heartbeat data. Here, the HF component is an indicator of parasympathetic nervous system activity and the activity level thereof changes depending on breathing, the LF component is an indicator of sympathetic nervous system activity and represents cognitive load for information processing, and the VLF component is related to body temperature regulation.

110 340 120 340 340 340 340 After Step S, the processormay calculate the brain health index representing the brain activity, brain flexibility, brain intelligence, and brain balance based on the brain wave data, and may calculate the mental health index representing the autonomic nerve activity, autonomic nerve balance, and stress based on the heartbeat data (S). More specifically, the processormay calculate the activation level for each frequency band from the brain activity data extracted from the brain wave data. The processormay calculate the activation level for each frequency band from the heart rate variability data extracted from heartbeat data. In addition, the processormay calculate the strength between a plurality of nodes constituting a brain network based on the brain activity data for each of the plurality of regions. The processormay calculate normalized LF, normalized HF, LF/HF ratio, or the like based on the heart rate variability data.

120 340 130 340 5 5 FIGS.A toF After Step S, the processormay provide a service interface screen that graphically visualizes the calculated brain health index and mental health index (S). That is, the processormay visually represent the brain activity, brain flexibility, brain intelligence, brain balance, autonomic nerve activity, autonomic nerve balance, and stress as illustrated in.

5 5 5 5 5 5 FIGS.A,B,C,D,E, andF are examples of the user interface screen for providing the mental health information through the user device according to one embodiment of the present disclosure.

5 FIG.A 11 12 Referring to, the service interface screen visualizing the brain health index may include a graphic objectrepresenting the average score values of the brain activity, brain flexibility, brain intelligence, and brain balance, respectively, and an explanation regionexplaining the basis of brain wave measurement and the method of calculating each score.

13 1303 1302 1301 1301 1303 1302 1304 1301 1303 1302 The service interface screen visualizing the brain health index may include the regionthat illustrates the result of calculating the user's brain activity. Specifically, the service interface screen may include a region that represents an activation levelfor each frequency bandof delta wave, theta wave, low-alpha, high-alpha, low-beta, middle-beta, high-beta, and gamma calculated based on the brain wave data (brain activity data) as a graphfor brain activity. In the graphfor brain activity, the activation levelfor each frequency bandis displayed in different colors to improve visibility, and the meaning of each indicator may be displayed in one region. In addition, a normal range regionis displayed on the reference axis representing the brain activation level in the graphfor brain activity, so that the user can recognize that the activation levelfor each frequency bandis not relative.

340 1305 1301 340 1306 In various embodiments, the processormay compare the brain activation level of each of the plurality of frequency bands with the reference value preset for each frequency band, and generate the diagnosis result related to the user's brain activity according to the comparison result. Accordingly, the service interface screen visualizing the brain health index may include a regionrepresenting the diagnosis result in a region adjacent to the graphfor the brain activity. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the brain activity falls into based on the comparison result, and include a graphic objectrepresenting the diagnosis result on the service interface screen.

14 1401 1402 1403 In addition, the service interface screen visualizing the brain health index may include a regionrepresenting the user's brain flexibility calculation result. Specifically, the service interface screen may include a region representing the connection strength between brain regions calculated based on the brain activity data as a continuous spectrum graphfor the brain flexibility. The continuous spectrum for the brain flexibility may be displayed in different colors according to the degree of flexibility (insufficient˜adequate˜excessive). The user's brain flexibility calculation result (connection strength)may be displayed at one point. In addition, a brain network imagecorresponding to reference values (insufficient/adequate/excessive) in the continuous spectrum for the brain flexibility may be displayed.

340 1404 1401 340 1405 In various embodiments, the processormay generate a brain flexibility-related diagnosis result based on the calculated result value for the brain flexibility. Accordingly, the service interface screen visualizing the brain health index may include a regionrepresenting the diagnosis result in a region adjacent to the continuous spectrum graphfor the brain flexibility. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculated result value for brain flexibility belongs to, and may include a graphic objectrepresenting the diagnosis result in the service interface screen.

5 FIG.B 15 1502 1501 340 1503 1501 340 1504 2 Referring to, a service interface screen visualizing the brain health index may include a regionillustrating a result of calculating a user's brain intelligence. Specifically, the service interface screen may include a region where a peak valuefor any one frequency band calculated based on the brain wave data (brain activity data) in a quadrant illustrating a frequency (Hz) and an output value (μV) of the frequency is represented as a graphfor the brain intelligence. In particular, the processormay calculate a peak value in an alpha wave (α) of 8 to 12 Hz, display the peak value on the service interface screen, and generate a diagnosis result based on the value. Accordingly, the service interface screen visualizing the brain health index may include a regionrepresenting the diagnosis result in the region adjacent to the graphfor the brain intelligence. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculated result value for brain intelligence falls into, and may include a graphic objectrepresenting the diagnosis result on the service interface screen.

16 1602 1601 1602 1601 1603 The service interface screen visualizing the brain health index may include a regionthat represents the user's brain balance calculation result. Specifically, the service interface screen may include a region that represents the prefrontal activation asymmetry indexcalculated based on the brain wave data as a semicircular scale graphfor the brain balance. The semicircular scales for the brain balance correspond to the degrees of left and right prefrontal activation, respectively, and these may be displayed in different colors according to the degrees of asymmetry. The user's prefrontal activation asymmetry indexmay point to a point of the semicircular scale graph, and the user's behavioral characteristic informationaccording to the asymmetry may be displayed at both ends. For example, when the prefrontal lobe is skewed to the left, the user may be represented with the characteristics of “excessive negative emotion, withdrawn, and behaviorally inhibited”, and when the prefrontal lobe is skewed to the right, the user may be represented with the characteristics of “excessive positive emotion, exploratory, and behaviorally active”.

340 1604 1601 340 1605 In various embodiments, the processormay generate the diagnosis result based on the brain balance calculation result. Accordingly, the service interface screen visualizing a brain health index may include a regionrepresenting a diagnosis result in a region adjacent to a semicircular scale graphfor the brain balance. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculation result for the brain balance falls into, and may include a graphic objectrepresenting the diagnosis result in the service interface screen.

5 FIG.C 17 18 Referring to, the service interface screen visualizing the mental health index may include a graphic objectrepresenting the average score values of autonomic nerve activity, autonomic nerve balance, and stress, and an explanation regionexplaining the basis for measuring heartbeat (heart rate variability) and the method for calculating each score.

19 1903 1901 1901 1903 1902 1904 1901 1903 1902 The service interface screen visualizing the mental health index may include a regionthat illustrates the result of calculating the user's autonomic nerve activity. Specifically, the service interface screen may include a region that represents the activation levelof each component of a very low frequency (VLF), a low frequency (LF), a high frequency (HF), and a total power (TF) (including VLF, LF, and HF) calculated based on the heart rate variability data as a graphfor autonomic nerve activity. In the graphfor the autonomic nerve activity, the activation levelof each componentmay be displayed in different colors to improve visibility, and the meaning of each indicator may be displayed in one region. In addition, a normal range regionmay be displayed on a reference axis representing the activation level of each component in the graphfor the autonomic nerve activity, to make the user aware that the activation levelof each frequency componentis not relative.

340 1905 1901 340 1906 In various embodiments, the processormay generate a diagnosis result related to autonomic nerve activation based on the activation level for each frequency component. Accordingly, the service interface screen visualizing the mental health index may include the regionrepresenting the diagnosis result in the region adjacent to the graphfor the autonomic nerve activity. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the autonomic nerve activity falls into, and include a graphic objectrepresenting the diagnosis result in the service interface screen.

20 2002 2001 2001 2002 2003 In addition, the service interface screen visualizing the mental health index may include the regionthat illustrates the result of calculating the user's autonomic nerve balance. Specifically, the service interface screen may include a region that illustrates the sympathetic and parasympathetic nerve activity calculated based on the heart rate variability data as a percentage ratioin a comparison graphfor the autonomic nerve balance. In the comparison graphfor the autonomic nerve balance, each percentage ratiois displayed as a bar scale, and abnormal phenomenon informationaccording to the imbalance of the sympathetic and parasympathetic nerve activity may be displayed at both ends. For example, when the sympathetic nerve activity is biased, the user may experience characteristics such as “anxiety, panic disorder, sleep disorder, excitement, tremors, constipation, and headache”, and when the parasympathetic nerve activity is biased, the user may experience characteristics such as “depression, lethargy, dizziness, decreased pulse, decreased blood pressure, diarrhea, and edema”.

340 2001 2005 340 2004 In various embodiments, the processormay generate the diagnosis result related to the autonomic nerve balance based on the calculation results of the sympathetic and parasympathetic nerve activities. Accordingly, the service interface screen visualizing the mental health index may include the comparison graphfor the autonomic nerve balance and a regionrepresenting the diagnosis result in an adjacent region. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculation ratio of the sympathetic and parasympathetic nerve activities belongs to, and may include a graphic objectrepresenting the diagnosis result in the service interface screen.

5 FIG.D 21 2101 2103 2102 2104 Referring to, the service interface screen visualizing the mental health index may include a regionthat represents a result of calculating a user's stress state. Specifically, the service interface screen may include a region that represents the stress index and the stress resistance calculated based on the heart rate variability data, respectively, as continuous spectrum graphsandfor the stress state. The continuous spectrum for the stress index and the stress resistance may be displayed in different colors according to the level (very low˜normal˜very high), and the user's stress indexand stress resistancemay be displayed at one point.

340 2105 2101 2103 340 2106 In various embodiments, the processormay generate the diagnosis result related to the stress state based on the calculation results for the stress index and the stress resistance. Accordingly, the service interface screen visualizing the mental health index may include a regionrepresenting the diagnosis result in the region adjacent to the continuous spectrum graphsandfor the stress state. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculation result for the stress state belongs to, and may include a graphic objectrepresenting the diagnosis result in the service interface screen.

22 23 2201 2203 2202 2204 In addition, the service interface screen visualizing the mental health index may include regionsandrepresenting the user's subjective psychological state results. Specifically, the service interface screen may include a region representing the depression index and the anxiety index, which are calculated in response to the user's psychological test result data, as continuous spectrum graphsandfor the subjective psychological state, respectively. The continuous spectrum for the depression index and the anxiety index may be displayed in different colors according to the degree (normal range˜mild˜moderate˜severe˜very severe), and the user's depression indexand anxiety indexmay be displayed at one point.

340 2205 2201 2203 340 2206 In various embodiments, the processormay generate a diagnosis result related to a subjective psychological state based on the calculation results for the depression index and the anxiety index. Accordingly, the service interface screen visualizing the mental health index may include a regionrepresenting the diagnosis result in the region adjacent to continuous spectrum graphsandfor the subjective psychological state. In particular, the processormay determine which of the five classification items (danger/caution/normal/good/very good) the calculation result for the subjective psychological state belongs to, and may include a graphic objectrepresenting the diagnosis result in the service interface screen.

340 2301 2302 2301 In various embodiments, the processormay generate a user's self-understanding value based on the heart rate variability data and the psychological test result data. Accordingly, the service interface screen visualizing the mental health index may include a continuous spectrum graphfor self-understanding divided into levels (low˜normal˜high), and may be configured to display the user's self-understandingvalue at one point on the continuous spectrum graph.

5 FIG.E 24 Referring to, the service interface screen may include a regionthat describes a rough response plan for the user by a comprehensive score range including a brain health index and a mental health index. For example, when the comprehensive score is 80 points or more, a response such as “you are in good health. maintain your current condition” is suggested, when the score is 60 to 80 points, a response such as “you need to pay attention to your health. take a short break” is suggested, and when the score is less than 60 points, a response such as “please consult a specialist” is suggested.

25 26 1306 1405 1504 1605 1906 2005 2105 2205 In addition, the service interface screen may include regionsandrepresenting the diagnosis results for each item of the brain health index and the mental health index. For example, the service interface screen may include graphic objects,,, andrepresenting the diagnosis results for brain activity, brain flexibility, brain intelligence, and brain balance, respectively, and graphic objects,,, andrepresenting the diagnosis results for autonomic nerve activity, autonomic nerve balance, stress state, and subjective psychological state, respectively.

5 FIG.F 27 29 28 30 Referring to, the service interface screen may include regionsandthat indicate an average value of the brain health index and the mental health index based on the user's gender and age. In addition, the service interface screen may further include regionsandthat indicate where the user's brain health index and mental health index fall in a score distribution graph based on the user's age group.

340 340 In various embodiments, the processormay classify the brain health index calculation results based on brain wave data for each type, and provide diagnosis results (for example, therapeutic suggestions from specialist) for each type through the service interface screen. Specifically, the processormay classify the types as illustrated in [Table 1] below by matching the brain health index and physical/emotional characteristics illustrated to the user as keywords.

TABLE 1 EEG type Description Therapeutic suggestions Foggy Brain wave activity is Brain activation (reading, Difficulty significantly low, so cognitive games, solving puzzles), concentrating, and thinking activities are hazy cognitive training, cognitive forgetfulness, as if covered in fog, and overall behavioral therapy, aerobic helplessness, dementia concentration is low. exercise that makes you sweat (more than 3 times a week, more than 30 minutes per session) Mindful Brain wave activity is No special suggestions Meditation, maintained high, so cognitive mindfulness, self- and thinking activities are regulation, control, regulated to a state where sleepiness excitement is excluded, and a calm state is maintained. Talented Brain wave activity is No special suggestions Concentration, maintained high, so not only is intelligence, smartness, the concentration high in gifted cognitive and thinking activities, but clarity and sparkling creativity stand out. Tension Brain wave activity is Mindfulness training, rest, Burden, tension, significantly high, so cognitive zoning out (fishing, staring at a compulsion, insomnia and thinking activities are fire, staring at water, looking at overloaded, and they are overly the sea), progressive muscle aroused and sensitive to various relaxation training, cognitive stimuli. behavioral therapy, light walking (more than 3 times a week, more than 30 minutes per session) Foggy-tense Brain wave activity is irregularly Rest, mindfulness training, Burden, tension, repeated between high and low, stability, light brain activation difficulty concentrating, so cognitive and thinking (reading, games, solving forgetfulness activities frequently alternate puzzles), cognitive training, light between hyperactivity and walking, and running (more than hypoactivity, so concentration is 3 times a week, more than 30 not maintained consistently. minutes per session), behavioral activation Stable Brain wave activity is No special suggestions Stability, balanced, appropriate, so cognitive and healthy thinking activities remain normally activated, overall concentration is maintained and higher-order cognition is possible.

340 340 In various embodiments, the processormay classify the results of calculating the mental health index based on the heartbeat data for each type, and provide the diagnosis results (for example, therapeutic suggestions from specialist) for each type through the service interface screen. Specifically, the processormay classify the types as illustrated in [Table 2] below by matching the mental health index and the physical/emotional characteristics illustrated to the user as keywords.

TABLE 2 PPG type Description Therapeutic suggestions Mind weak The autonomic nervous system Rest, travel, mindfulness Palpitations, shortness of is generally weak, so the ability training, light walking, breath, depression, to cope with changes in the behavioral activation, sweating, indigestion, external environment and stress supportive counseling, headaches is relatively low. aerobic exercise Weak-depressive The state is a state of lethargy in Stability, rest, light walking, Decreased energy, which the autonomic nervous supportive counseling, lethargy system is generally weak, aerobic exercise, mindfulness physiological balance is broken, training, behavioral and the ability to cope with activation, meeting a changes in the external psychiatrist environment and relieve stress is reduced. Weak-anxious The autonomic nervous system Stability, rest, light walking, Excessive anxiety, tension, is generally weak and progressive muscle relaxation and impulsiveness physiologically unbalanced, and training, mindfulness is very sensitive to changes in training, cognitive behavioral the external environment and therapy, behavioral stress, causing excessive tension. activation, and meeting a psychiatrist Anxious The physiological balance of the Stability, rest, progressive Anxiety, tension autonomic nervous system is muscle relaxation training, disrupted, making it easily mindfulness training, affected by the external cognitive behavioral therapy, environment and stress, light walking, and meeting a accompanied by acute mental health specialist psychogenic symptoms such as anxiety and excitement. Depression The physiological balance of the Stability, rest, light walking, Depression, lethargy autonomic nervous system is aerobic exercise, mindfulness disrupted, leading to a decline in training, cognitive behavioral overall health and bioenergy therapy, behavioral accumulated by the external activation, meeting a mental environment and stress, and health specialist persistent depression. Stable The autonomic nervous system No special suggestions Stability, balance, health is in physiological balance, so it responds quickly and appropriately to the external environment and stress, and is stably regulated.

300 340 300 So far, the mental health information providing deviceof the present disclosure and the user interface providing method for providing mental health information performed by the processorof the mental health information providing devicehave been roughly explained. According to the present disclosure, by numerically expressing a person's mental and mental state as a brain health index and a mental health index, it can help a medical professional's quick evaluation (diagnosis), and further, it can be utilized as a means for preventing diseases and accidents (for example, health checkup records for insurance subscription) according to the user's current state. In addition, by simplifying and expressing a professional diagnosis region as a graph, it can help the user's understanding of the current mental health state. Although the embodiments of the present disclosure have been described in more detail with reference to the attached drawings, the present disclosure is not necessarily limited to these embodiments, and can be variously modified and implemented within a scope that does not depart from the technical idea of the present disclosure. Therefore, the embodiments disclosed in the present disclosure are not intended to limit the technical idea of the present disclosure, but to explain, and the scope of the technical idea of the present disclosure is not limited by these embodiments. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive. The protection scope of the present disclosure should be interpreted by the claims below, and all technical ideas within the scope equivalent thereto should be interpreted as being included in the scope of the rights of the present disclosure.